RAG e conhecimento
second-brain-os
A self-maintaining AI second brain for Obsidian and Claude Code.
★ 888 estrelasMIT
Ver o guia →ontosphere é um projeto de RAG e conhecimento de código aberto de ThHanke (ThHanke/ontosphere no GitHub). Tem 247 estrelas no GitHub e 30 forks, é publicado sob a licença NOASSERTION e foi atualizado pela última vez no GitHub em 24 de setembro de 2026.
Edit RDF knowledge graphs in your browser — no backend needed.
Decide what you want the project to do before installing anything.
Grab the source and skim the README for setup requirements.
Install dependencies and add any API keys or settings it needs.
Launch it and follow the example workflow from the docs.
Exposes its capabilities to AI agents over the Model Context Protocol.
Structures information as a queryable graph.
Bring notes from Obsidian, Notion, and more.
Own your second brain completely.
Combines keyword and semantic retrieval.
Connects notes into a queryable graph.
Download the source and move into the project folder.
git clone https://github.com/ThHanke/ontosphere.git
cd ontospherePull in the Node packages the project needs.
npm installStart the dev server and open the printed URL.
npm run devIt is an open-source project at ThHanke/ontosphere with 30 forks. Check the repo’s contributors and recent commits to judge how active maintenance is.
GitHub does not assert a license for this repo, so treat the code as all rights reserved until the author adds one.
Locally or on your own server, depending on how you deploy it.
Most support OpenAI, Anthropic, Ollama, and other providers via config.
Yes — MCP support lets agents search your knowledge base directly.
A self-maintaining AI second brain for Obsidian and Claude Code.
An open-source knowledge base for people and AI agents.
A Flutter e-reader and audiobook app with AI chat.
RAG for your monorepo: query, understand and edit multi-language codebases with a knowledge graph.
Build Neo4j knowledge graphs from unstructured data using LLMs — then chat with your graph.
A knowledge-base platform with visual AI workflows — build Q&A systems on your own documents
Os outros projetos de RAG e conhecimento com mais estrelas no catálogo do LibreAI — a lista realista de alternativas se ontosphere não for o ideal para você.
Build Agentic workflows, RAG pipelines, with rich AI model and tool support on one collaborative workspace. Deploy on cloud, VPC, or…
RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context…
Lightweight OCR toolkit turning PDFs and images into structured, LLM-ready data in 100+ languages
MinerU — turns PDFs and Office documents into LLM-ready Markdown and JSON for agents and RAG pipelines, Apache-2.0 plus terms
Stop renting your intelligence. Own it with AnythingLLM. Everything you need for a powerful local-first agent experience
Projetos de RAG e conhecimento próximos no catálogo, os mais próximos em estrelas de ontosphere: continue explorando dos dois lados dele.
Self-hosted rag & knowledge: 🧠 the brain for your ai — local-first memory engine for.
Semantic search engine designed for files and code.
Render and deploy a folder of markdown as a site in one move.
PDF reader with AI chat, flashcards, annotations, and text-to-speech.
AI-native data platform: 60+ connectors, ETL, scheduling, and RAG search.
Turn your GitHub stars into a searchable AI knowledge base.
Grátis e aberto: pegue o código-fonte, dê uma estrela no repositório e comece a criar.